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All Journal SAMUDERA Jurnal Transformatika Jurnal Edukasi dan Penelitian Informatika (JEPIN) CESS (Journal of Computer Engineering, System and Science) INFORMAL: Informatics Journal InfoTekJar : Jurnal Nasional Informatika dan Teknologi Jaringan JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING JOURNAL OF APPLIED INFORMATICS AND COMPUTING METHOMIKA: Jurnal Manajemen Informatika & Komputerisasi Akuntansi Jurnal Sisfokom (Sistem Informasi dan Komputer) ILKOM Jurnal Ilmiah Jurnal Nasional Pendidikan Teknik Informatika (JANAPATI) JISKa (Jurnal Informatika Sunan Kalijaga) JURNAL Al-AZHAR INDONESIA SERI SAINS DAN TEKNOLOGI Jurnal Informasi dan Teknologi JTIK (Jurnal Teknik Informatika Kaputama) Jurnal Sistem Komputer dan Informatika (JSON) Jurnal Pengabdian kepada Masyarakat Nusantara Jurnal Computer Science and Information Technology (CoSciTech) International Journal of Engineering, Science and Information Technology Multica Science and Technology jeti TECHSI - Jurnal Teknik Informatika Sisfo: Jurnal Ilmiah Sistem Informasi International Journal of Information System & Innovative Technology Multidisiplin Pengabdian Kepada Masyarakat (M-PKM) Jurnal Malikussaleh Mengabdi Journal of Advanced Computer Knowledge and Algorithms Scientific Journal of Informatics International Journal of Information System and Innovative Technology Smatika Jurnal : STIKI Informatika Jurnal Proceedings of International Conference on Multidisciplinary Engineering (ICOMDEN)
Rozzi Kesuma Dinata
Program Studi Teknik Informatika, Unversitas Malikussaleh, Aceh Utara 24351, Indonesia
Religion Agriculture, Biological Sciences & Forestry Humanities Astronomy Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Nursing Physics Public Health Social Sciences Transportation Other

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CLASSIFICATION OF COLOR BLIND STUDENTS AT SMA NEGERI 1 LHOKSEUMAWE USING NAÏVE BAYES ALGORITHM Rozzi Kesuma Dinata; Maryana; Sujacka Retno; Gadis Ayu Sofiana
Multica Science and Technology Vol 3 No 1 (2023): Multica Science and Technology
Publisher : Universitas Mulia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47002/mst.v3i1.425

Abstract

This research aims to classify students and determine eye conditions with normal and partial color blindness by using Naïve Bayes algorithm. The research dataset was obtained from students at SMA Negeri 1 Lhokseumawe. The variables used in this research were 24 Plate Ishihara Tests with data collection techniques by using interviews, literature studies and questionnaires. Total data in this research are 140 data and divided into 110 training data and 30 testing data. The results showed that from 110 data trained, there were 69 students included in the normal group and 41 students included in the partial group. Then, the 30 testing data were tested into the classification system for color blind students using Naïve Bayes Algorithm. The accuracy level of the test results was 86.67% and 13.33% error.
SISTEM E-ARSIP SURAT BERBASIS WEB PADA DINAS KOMUNIKASI INFORMATIKA DAN PERSANDIAN KAB. ACEH TAMIANG Retno, Sujacka; Dinata, Rozzi Kesuma; Alfika, Selly
Sisfo: Jurnal Ilmiah Sistem Informasi Vol. 6 No. 2 (2022): Sisfo: Jurnal Ilmiah Sistem Informasi, Oktober 2022
Publisher : Universitas Malikussaleh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29103/sisfo.v6i2.10296

Abstract

Arsip adalah catatan rekaman kegiatan atau sumber informasi dengan berbagai macam bentuk yang dibuat oleh lembaga, organisasi maupun perseorangan dalam rangka pelaksanaan kegiatan. Tidak terkecuali pada sistem arsip kedinasan untuk menandai surat masuk dan surat keluar yang masih bersifat manual, dimana hal ini sangat tidak efesien karena surat masuk maupun surat keluar yang ada bisa saja terselip, hilang dan robek. Oleh karena itu sangat perlu untuk merubah sistem arsip manual menjadi sistem arsip berbasis web supaya membantu proses penyimpanan data surat. Sehingga dapat meningkatkan kualitas sistem pada layanan arsip surat. Dalam penelitian ini akan dirancang sebuah sistem arsip surat berbasis web.
Online Newspaper Clustering in Aceh using the Agglomerative Hierarchical Clustering Method Tjut Adek, Rizal; Kesuma Dinata, Rozzy; Ditha, Ananda
International Journal of Engineering, Science and Information Technology Vol 2, No 1 (2022)
Publisher : Malikussaleh University, Aceh, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (368.616 KB) | DOI: 10.52088/ijesty.v2i1.206

Abstract

The rapid progress in the field of information technology, especially the internet, has given birth to a lot of information. The ease of publishing an article on a website causes an explosion of news pages which will certainly confuse readers. The diversity and the increasing number of news articles make it increasingly difficult for internet users to find news and large piles of news data on online newspaper sites in Aceh. The grouping of text documents is needed to classify news in online newspapers in Aceh based on the content contained in news articles. In this study, the process of grouping online news in Aceh was tried using the Agglomerative Hierarchical Clustering method. News is grouped with a Bottom-Up design strategy that starts with placing each object as a cluster then combined into a larger cluster based on the similarity of keywords in each news, then the cluster results are compared and put into each news category. The research design was carried out in a structured manner using data flow diagrams in forming the research framework. The study was conducted by taking online news text data on 10 online news websites in Aceh from July 2016 to March 2017 with 1000 randomly generated documents. The process of crawling news data is done using a php script which will only take text files from the news on the website. News grouping is done based on religion, politics, law, sports, tourism, education, culture, economy and technology. The results of the grouping performance of the Agglomerative Hierarchical Clustering method in this study have an average accuracy of 89.84%.
Meningkatkan Penulisan Karya Tulis Ilmiah dan Publikasi Guru di SMA Negeri 1 Lhokseumawe Ula, Mutammimul; Badriana, Badriana; Dinata, Rozzi Kesuma; Bintoro, Andik; Fuadi, Wahyu
Jurnal Malikussaleh Mengabdi Vol. 2 No. 1 (2023): Jurnal Malikussaleh Mengabdi, April 2023
Publisher : LPPM Universitas Malikussaleh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29103/jmm.v2i1.12357

Abstract

Peningkatan penulisan karya tulis ilmiah guru dapat dilihat dari berapa banyaknya tulisan/karya yang dihasilkan yang sesuai kompetensi yang dimiliki. Guru tidak hanya mengajar siswa di kelas namun juga dituntut untuk dapat menuliskan gagasan atau ide yang dapat dituangkan dalam tulisan yang dipublish di buku maupun jurnal ilmiah baik itu terakreditasi nasional maupun internasional. Salah satu ragam Dewasa ini kompetensi seseorang bisa dilihat dari berapa banyaknya tulisan yang dia buat sesuai kompetensi yang dimiliki. Tujuan pengabdian ini adalah untuk dapat meningkatkan kemampuan menulis dan pengembangan profesi guru yang dipublish di buku maupun jurnal ilmiah baik itu terakreditasi nasional maupun internasional. Metode pelaksanaan pengabdian ini dengan menggunakan library research. Dengan adanya pelaksaan pengabdian ini dapat meningkatkan kemampuan profesionalisme guru sekaligus memperbaiki kualitas pembelajaran dalam mengajar dengan siswa dikelas. selanjutnya publikasi ilmiah bagi guru sebagai prasyarat dalam kenaikan pangkat dan jabatan sehingga memberikan motivasi yang lebih kepada guru untuk dapat membuat karya ilmiah yang lebih berkualitas. Hasil dari pelaksanaan pengabdian ini Dapat menjadi acuan dalam membuat publikasi guru dan dapat menjadi salah satu syarat kenaikan pangkat dan jabatan guru. Eksistensi kompetensi guru bersangkutan dan juga mengembangkan dan menyebarluaskan keilmuan. Kemudian dengan adanya  pelatihan penulisan karya ilmiah bagi guru-guru dapat meningkatkan publikasi imiah bagi guru-guru tersebut. Kegiatan ini dapat membantu peserta guru dalam  menyusun  dan  memperbaiki kerangka  artikel  yang telah dibuat sebelumnya sehingga telah disertakan materi dan wawasan secara teknis maupun teoretis mengenai cara menulis jurnal yang akan diterbitkan jurnal nasional akreditasi.
Analysis of the Topsis in the Recommendation System of PPA Scholarship Recipients at Universitas Islam Kebangsaan Indonesia Hasdyna, Novia; Dinata, Rozzi Kesuma; Retno, Sujacka
Jurnal Transformatika Vol 21, No 1 (2023): July 2023
Publisher : Jurusan Teknologi Informasi Universitas Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26623/transformatika.v21i2.7051

Abstract

This research implements the TOPSIS method on a recommendation system for Peningkatan Prestasi Akademik (PPA) scholarship recipients. The research data was obtained from the computer and multimedia faculty, UNIKI. The results showed that the TOPSIS method can provide the best alternative based on the highest rank. In this research, the highest rank was obtained from the results for predetermined criteria, namely GPA, achievements, parental dependents and parental income. The highest value obtained is 0.7489. The system built based on a website with the PHP programming language.
Classification of Heart Disease Using Modified K-Nearest Neighbor (MKNN) Method Lubis, Aulia Azzahra Ma'aruf; Dinata, Rozzi Kesuma; Aidilof, Hafizh Al Kautsar
Journal of Advanced Computer Knowledge and Algorithms Vol 1, No 2 (2024): Journal of Advanced Computer Knowledge and Algorithms - April 2024
Publisher : Department of Informatics, Universitas Malikussaleh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29103/jacka.v1i2.15702

Abstract

Penyakit jantung memiliki banyak jenis dan gejala yang dialami. Penyakit jantung adalah sebuah kondisi ketika organ jantung tidak dapat bekerja sebagaimana fungsinya dengan baik. Jantung adalah organ penting dalam tubuh manusia yang dimana fungsinya adalah memompa darah ke seluruh tubuh. Karena itu dibutuhkannya diagnosa awal untuk pencegahan penyakit jantung dengan memanfaatkan system yang dapat dibuat untuk diagnosa awal pada gejala yang dialami. Yang pada penelitian ini akan menggunakan metode Modified K-Nearest Neighbor (MKNN) dalam mengklasifikasikan penyakit jantung berdasarkan kriteria atau gejala yang ada. Penelitian ini menggunakan 6 kriteria penyakit dan 3 kelas diagnosa penyakit jantung. Dengan melewati beberapa langkah pengerjaan yaitu menghitung jarak Euclidean, menghitung nilai validitas dan terakhir menghitung weight voting dengan mengandalkan nilai K yang telah ditentukan sejak awal perhitungan. Pada penelitian ini telah ditentukan nilai K=5 dan didapat hasil pengujian akurasi sebesar 85%, dengan recall 90% dan precision 85%.
Implementation of Data Mining for Vertigo Disease Classification Using the Support Vector Machine (SVM) Method Jasmin, Nadya; Dinata, Rozzi Kesuma; Sahputra, Ilham
Journal of Advanced Computer Knowledge and Algorithms Vol 1, No 4 (2024): Journal of Advanced Computer Knowledge and Algorithms - October 2024
Publisher : Department of Informatics, Universitas Malikussaleh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29103/jacka.v1i4.17807

Abstract

This research aims to implement advanced data mining techniques for the classification of vertigo disorders using the Support Vector Machine (SVM) method. Vertigo, characterized by a spinning sensation, can be triggered by various factors such as nervous system disorders and inner ear infections. With the rising prevalence of vertigo patients, there is a pressing need for more effective and efficient diagnostic tools. This study was conducted at Puskesmas Jangka in Bireuen Regency, involving the collection of vertigo patient data from the years 2023-2024. The collected data underwent a comprehensive preprocessing pipeline, including data cleaning, partitioning into training and testing datasets, and subsequent implementation of the SVM algorithm. The performance of the model was evaluated using the Mean Absolute Percentage Error (MAPE), resulting in a MAPE value of 28.47%.
Penerapan Algoritma Random Forest dalam Deteksi dan Klasifikasi Ransomware Alvanof, Mulia; Bustami; Rozzi Kesuma Dinata
Jurnal Elektronika dan Teknologi Informasi Vol 5 No 2 (2024): September 2024
Publisher : LPPM-UNIKI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5201/jet.v5i2.488

Abstract

Ransomware is a type of malware that blocks access to computer systems or data until a ransom is paid by the victim. Ransomware attacks typically occur due to malicious files that are unknowingly downloaded and installed by the victim onto their computer system. Given the threats and potential losses posed, methods for detecting and classifying ransomware continue to be developed, one of which utilizes the Random Forest machine learning algorithm. Random Forest is chosen for its advantages in handling large datasets, short training time, high prediction accuracy, and its ability to reduce the risk of overfitting. Using 1380 ransomware samples from a dataset with 54 features, 10 best features were selected through Feature Selection where the built Random Forest model successfully predicted ransomware files with an accuracy of 98.79%.
Evaluating The Quality of K-Medoids Clustering on Crime Data in Indonesia Sujacka Retno; Rozzi Kesuma Dinata; Novia Hasdyna
METHOMIKA: Jurnal Manajemen Informatika & Komputerisasi Akuntansi Vol. 8 No. 2 (2024): METHOMIKA: Jurnal Manajemen Informatika & Komputersisasi Akuntansi
Publisher : Universitas Methodist Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46880/jmika.Vol8No2.pp274-280

Abstract

This study evaluates the quality of K-Medoids clustering applied to criminal incident data in Indonesia from 2000 to 2023. The analysis compares the clustering performance on both original and normalized datasets using various evaluation metrics, including the Davies-Bouldin Index (DBI), Silhouette Score (SS), Normalized Mutual Information (NMI), Adjusted Rand Index (ARI), and Calinski-Harabasz Index (CH). The findings reveal that the original dataset consistently outperforms the normalized dataset across all metrics. The optimal clustering was achieved in the seventh iteration of the original data, with the lowest DBI (0.438), the highest SS (0.683), NMI (0.916), ARI (0.984), and CHI (57.418). In contrast, the normalized data exhibited higher DBI values and, in some cases, negative Silhouette Scores, indicating less distinct clusters. These results suggest that for this dataset, K-Medoids clustering performs more effectively on the original data without normalization, providing more accurate and well-defined clusters of criminal incidents. This insight is crucial for future research and practical applications in crime data analysis, emphasizing the importance of dataset preprocessing in clustering methodologies.
Enhancing K-Means Clustering Model to Improve Rice Harvest Productivity Areas in Aceh Utara Using Purity Sujacka Retno; Bustami; Rozzi Kesuma Dinata
Jurnal Nasional Pendidikan Teknik Informatika : JANAPATI Vol. 13 No. 2 (2024)
Publisher : Prodi Pendidikan Teknik Informatika Universitas Pendidikan Ganesha

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23887/janapati.v13i2.78254

Abstract

To optimize the performance of the clustering process using K-Means, an optimalization approach employing the Purity algorithm is needed. This research was tested on a dataset of rice harvest productivity areas in Aceh Utara Regency by comprehensively analyzing the number of iterations and the DBI values produced by K-Means and Purity K-Means in clustering priority and non-priority rice production areas. This is in line with the efforts of the Regional Government to implement rice production intensification programs in Aceh Utara Regency. From the testing of Purity K-Means, an average of 5, 2, 2, 5, and 3 iterations were obtained from all tested datasets sequentially from 2019 to 2023. Meanwhile, from the testing of conventional K-Means, the average number of iterations obtained was 5.4, 4.8, 4.2, 5.6, and 3.8 iterations, sequentially. This indicates that the clustering performance conducted by Purity K-Means is better than conventional K-Means. The DBI values obtained from Purity K-Means for the entire dataset sequentially are 0.6781, 0.4175, 0.4419, 0.6182, and 0.4973. This value is lower compared to the DBI values obtained from conventional K-Means, which are 0.7178, 0.6025, 0.4971, 0.7222, and 0.5519, respectively. This also indicates that the validity level of the clustering results performed by Purity K-Means is higher than conventional K-Means.
Co-Authors ., Yustizar Abdillah, Ahmad Fauzi Aidilof, Hafizh Al Kautsar Akbar, Hafizal Akram, Rizalul Alfika, Selly Alvanof, Mulia Andik Bintoro Annisa Afrilia Zahra Annisa Ar Razi Ar Razi, Ar Razi Ardiansyah, Sakha Arif, M. Arif Saputra Arnawan Hasibuan Asrianda Asrianda Azrai Putra Barumun Daulay Badriana, Badriana Berutu, Indah Fachlira Bustami Bustami Bustami Bustami Bustami Ditha, Ananda Eva Darnila Fadhilah, Cut Fadlisyah Fadlisyah Fajri, T Irfan Fajriana, Fajriana Fiasari, Fiasari Fikria, Putri Fuadi, Wahyu Gadis Ayu Sofiana Hafizal Akbar Haried Novriando Hasan Tahir Hasmar, Muhammad Al Hafiz Irfan Fajri, T. Irwanda Syahputra Iswari, Syahyana Jasmin, Nadya Khairul Muttaqin Khairunnisa Khairunnisa Khairunnisa Khairunnisa Lubis, Aulia Azzahra Ma'aruf Maryana Maryana Maryana, Maryana Muhammad Al Hafiz Hasmar Muhammad Alif Muhammad Arasyi Muhammad Fikry Muhammad Iqbal Muhammad Nurfahmi Muhammad Rivai MUHAMMAD RIZAL Munirul Ula Mursyidah Mursyidah Mutammimul Ula Mutasar Muttaqin Muttaqin Nisak, Rahmatin Novia Hasdyna Novianda Novianda Nur Azizah Nurwijayanti Putra Barumun Daulay, Azrai Putri, Anya Regina Rahmat Hidayat Rahmat Hidayat Risawandi, Risawandi Rizki Suwanda Rizky Fasya Ramdhani Safwandi Safwandi Safwandi Safwandi Sahputra, Ilham Said Fadlan Anshari Suci Ramadani Sujacka Retno T Irfan Fajri Tahir, Hasan Taskia, Narita Tjut Adek, Rizal Ulfa, Septia Mulya Yafis, Balqis Yesy Afrillia Zahratul Fitri Zara Yunizar Zuboili, Zuboili Zulfa Zulfa